Action-Graph Games

Jiang, Albert Xin; Leyton‐Brown, Kevin; Bhat, Navin A. R.

doi:10.1016/j.geb.2010.10.012

Cited by 60 publications

(73 citation statements)

References 44 publications

(48 reference statements)

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“…Action-graph games [8] achieve compactness by exploiting several kinds of structure in the payoffs. The first kind of structure is anonymity, which means that an agent's payoff depends only on his own action and the "configuration" induced by the other agents-a tuple of counts of how many agents played each action.…”

Section: Action-graph Gamesmentioning

confidence: 99%

“…Note that there is a more complicated family of AGGs, AGGs with function nodes (described in detail in [8]). The algorithms described in this paper also work (and have the same asymptotic performance) with function nodes, but we omit the description of these games for notational clarity and simplicity.…”

Section: Action-graph Gamesmentioning

confidence: 99%

“…There is an extensive literature on compactly representing interesting games [19,9,12]. Action-graph games [8] (AGGs) unify these past representations and can furthermore represent many additional families of games in polynomial space. Computing solution concepts (e.g., Nash equilibrium) of compactly represented games is an active area of research.…”

Section: Introductionmentioning

confidence: 99%

“…Although in some cases novel algorithms have been proposed [4,20], a particularly fruitful approach has been to take existing, normal-form-based algorithms, and modify them to operate efficiently with a compact representation [2,1]. Indeed, the state-of-the-art Nash-equilibrium-finding algorithms for AGGs are normal-form algorithms with AGG-optimized expected-utility calculations [8].…”

Section: Introductionmentioning

confidence: 99%

“…1. An action graph for the "ice cream game" [8]. In the ice cream game, each player has either chocolate (C) or vanilla (V) ice cream to sell and must choose one of four possible locations to set up his stand.…”

Section: Introductionmentioning

confidence: 99%

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Computing Nash Equilibria of Action-Graph Games via Support Enumeration

Thompson

Leung

Leyton‐Brown

2011

Lecture Notes in Computer Science

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Abstract. The support-enumeration method (SEM) for computation of Nash equilibrium has been shown to achieve state-of-the-art empirical performance on normal-form games. Action-graph games (AGGs) are exponentially smaller than the normal form on many important classes of games. We show how SEM can be extended to the AGG representation, yielding an exponential improvement in worst-case runtime. Empirically, we demonstrate that our AGG-optimized SEM algorithm substantially outperforms the original SEM, and also outperforms state-of-the-art AGG-optimized algorithms on most problem distributions.

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Section: Action-graph Gamesmentioning

confidence: 99%

Section: Action-graph Gamesmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Computing Nash Equilibria of Action-Graph Games via Support Enumeration

Thompson

Leung

Leyton‐Brown

2011

Lecture Notes in Computer Science

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Game‐based cross‐layer channel allocation with SVC‐encoded multimedia streams in cognitive radio networks

Kuo

2012

Int J Network Mgmt

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The available unlicensed spectrum is increasingly being used by new wireless technologies, but past measurements show that the licensed spectrum is extremely underutilized. To address this issue, the IEEE 802.22 Working Group is developing a novel wireless air interface standard based on cognitive radios (CRs), i.e. IEEE 802.22 wireless regional area networks (WRANs). Moreover, over the last decade wireless multimedia applications have developed rapidly, raising significant concerns about the quality of service (QoS) of multimedia stream transmissions. In particular, the Joint Video Team (JVT) and ITU-T Video Coding Experts Group (VCEG) jointly proposed Scalable Video Coding (SVC) as the next-generation multimedia compression standard. However, the current IEEE 802.22 WRAN draft does not specify QoS mechanisms for SVC-encoded multimedia stream transmission in CR networks. To resolve this problem, we developed a cross-layer channel allocation algorithm (CLCAA) and a novel media access control (MAC) protocol to work with the algorithm. The CLCAA adapts to the characteristics of multimedia traffic and variations of wireless channels by determining the weighting of source-destination pair, which is determined by the deadlines of SVC-encoded multimedia streams, the queuing delay and channel conditions. The CLCAA then allocates transmission opportunities to source-destination pairs based on their weightings and game theory. We also conducted extensive simulations to demonstrate the efficiency of the CLCAA scheme. The simulation results show that the CLCAA scheme not only guarantees QoS for multimedia traffic but also achieves fairness across different streams.

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Treewidth and Pure Nash Equilibria

Thomas

Leeuwen

2013

Parameterized and Exact Computation

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Action-Graph Games

Cited by 60 publications

References 44 publications

Computing Nash Equilibria of Action-Graph Games via Support Enumeration

Computing Nash Equilibria of Action-Graph Games via Support Enumeration

Game‐based cross‐layer channel allocation with SVC‐encoded multimedia streams in cognitive radio networks

Treewidth and Pure Nash Equilibria

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